Consumers regularly consult information relating to almost any topic on the World Wide Web. However, a large volume of information is returned to the consumer with an unpredictable quality. In order to qualify the information, different technologies have been developed.
For example, U.S. Pat. No. 2009/0125382 provides an indication of a data source's accuracy with respect to past expressed opinions. The data source is assigned with predication scores based on the verified credibility of historical documents. A reputation score is assigned for a new document as a function of the predication scores from the historical documents, data source affiliations, document topics and other parameters.
Another example is U.S. Pat. No. 7,249,380 providing a model to evaluate trust and transitivity of trust of online services. The trust attributes are categorized in three categories, which relate to contents, owner of the web document and the relationships between the web document and certificate authorities.
U.S. Pat. No. 8,423,424 describes a web page fact-checking system of information and/or characterizes the information by comparing the information with one or more sources.
U.S. Pat. No. 7,809,721 describes a system for ranking data including three calculations: firstly, the quantitative semantic similarity score calculation which shows the qualitative relevancy of the particular location to the query; secondly, the general quantitative score calculation which comprises a semantic similarity score, a distance score and a rating score; thirdly, the addition of the quantitative semantic similarity score and the general quantitative score to obtain a vector score.
However, all the existing methods work in a passive mode: the calculation is carried out only when a query is launched. These technologies take a long time for the calculation and are not optimized for the dynamic update of the information on the World Wide Web. In the context of the fast development of social networks in particular, all users can constantly update information by broadcasting comments through all types of media.
Technical difficulties result in a huge number of data and information sources that have to be taken into account in order to calculate a relevant score, with the additional difficulty of the continuously changing scope of information. Calculating the score on the fly for a document requested by a user would require too many resources and time. Furthermore, attributing a score to each document that may be requested by a user and refreshing all these scores every time a new document or information becomes available is also too complicated.